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Kakapo: unsupervised outlier detection and integration with mlflow

Project description

Contributing to Kakapo

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Overview

We happily welcome contributions to Kakapo as long as CLA has been accepted. We use GitHub Issues to track community reported issues and GitHub Pull Requests for accepting changes.

Repository structure

The repository is structured as follows:

  • .github CICD for both kakapo and for solution examples.
  • python/kakapo/ Kakapo python module and tests. This code is used to build databricks-kakapo pip dependency.
  • docs/ Source code for documentation. Documentation is built via sphinx.

Test & build Kakapo

Python

The python bindings can be tested using unittest.

  • Move to the python/ directory and install the project and its dependencies: pip install .
  • Run the tests using unittest: python -m unittest

The project wheel file can be built with build.

  • Install the build requirements: pip install build wheel.
  • Build the wheel using python -m build.
  • Collect the .whl file from python/dist/

Documentation

The documentation has been produced using Sphinx.

To build the docs:

  • Install the pandoc library (follow the instructions for your platform here).
  • Install the python requirements from docs/docs-requirements.txt.
  • Build the HTML documentation by running make html from docs/.
  • You can locally host the docs by running the reload.py script in the docs/source/ directory.

Style

Tools we use for code formatting and checking:

  • scalafmt and scalastyle in the main scala project.
  • black and isort for the python bindings.

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